cycle (version 1.26.0)

fourierscore: Calculation of the Fourier score

Description

The function calculates fourier score for a chosen periodicity.

Usage

fourierscore(eset,T,times=seq_len(ncol(eset)))

Arguments

eset

object of the class “ExpressionSet”

T

length of chosen period

times

measurement times (with the index of the column as default)

Value

eset

Details

The Fourier score can be used to detect periodic signals. The closer a gene's expression follows a (possibly shifted) cosine curve of period T, the larger is the Fourier score. Mathematical details can be found in the given reference. The function fourierscore calculates the Fourier scores for all features of an ExpressionSet object.

References

Matthias E. Futschik and Hanspeter Herzel (2008) Are we overestimating the number of cell-cycling genes? The impact of background models on time series analysis, Bioinformatics, 24(8):1063-1069

Examples

# Data preprocessing 
if (interactive()){
set.seed(1)
data(yeast)  # loading the reduced CDC28 yeast set (from the Mfuzz package)
yeast <- yeast[1:600,]  # for illustration 
yeast <- filter.NA(yeast) # filters genes with more than 25% of the expression values missing 
yeast  <- fill.NA(yeast) # for illustration only; rather use knn method for 
yeast <- standardise(yeast)

T.yeast <- 85   # cell cycle period (t=85min)
times.yeast <-  pData(yeast)$time  # time of measurements

F <- fourierscore(yeast,T = T.yeast, times= times.yeast) 
# calculates the Fourier scores for yeast genes 

# Plot highest scoring gene
plot(times.yeast,exprs(yeast)[order(-F)[1],],type="o",
     xlab="Time",ylab="Expression",
     main=featureNames(yeast)[order(-F)[1]])

# Plot lowest scoring gene
plot(times.yeast,exprs(yeast)[order(F)[1],],type="o",
     xlab="Time",ylab="Expression",
     main=featureNames(yeast)[order(F)[1]])
}